The long-term objective is to improve recruitment, adherence and retention in clinical trials particularly among hard-to-reach populations of women, minorities and intravenous drug users. The specific aims of this study are as follows: (1) To determine if sociodemographic factors influence participation in clinical trials for HIV-related drugs; (2) After accounting for sociodemographic factors, to determine if type of clinical trial, HIV-related medical status, and behavioral factors influence agreement to participate in a clinical trial among a population of persons invited to participate; (3) To develop a psychosocial profile of clinical trial participants, including knowledge, attitudes and behavior associated with recruitment, adherence and retention in clinical trials. And, in an exploratory way, to investigate psychosocial and attitudinal factors among persons who decline participation in a clinical trial; (4) Prospectively, to determine which of the above sociodemographic, medical, behavioral or psychosocial factors (and combinations of factors) predict adherence and retention in clinical trials among those enrolled; (5) To examine whether participation in clinical trials, per se, influences health-relevant attitudes, behavior, and outcomes. Data will be collected from HIV/AIDS patients who agree (experimental group) and disagree (comparison group) to participate in clinical trials. Data will be gathered from existing medical records for all subject (N=400-500). In addition, interviews will be conducted by a trained clinical interviewer: 1 interview with a select group of comparison group members (n=100), and 3 interviews over the course of the clinical trial for the experimental group members (n=100). All experimental group members will be interviewed at enrollment and 3 months post-enrollment to enable comparative prospective analysis; the timing of a third interview is dependent on type of trial (phase I vs. II/III) and completion versus termination of trial. A series of hierarchical logistic regression models will be used to analyze these data.